Many organizations collect large amounts of transactional and time series data related to activities, such as time stamped data associated with physical processes, such as product manufacturing or product sales. These large data sets may come in a variety of forms and often originate in an unstructured form that may include only a collection of data records having data values and accompanying time stamps.
Organizations often wish to perform different types of time series analysis on their collected data sets. However, certain time series analysis operators (e.g., a predictive data model for forecasting product demand) may be configured to operate on hierarchically organized time series data. Because an organization's unstructured time stamped data sets are not properly configured, the desired time series analysis operators are not able to properly operate on the organization's unstructured data sets.